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Development of Digital Image Processing as an Innovative Method for Activated Sludge Biomass Quantification
Activated sludge process is the most common method for biological treatment of industrial and municipal wastewater. One of the most important parameters in performance of activated sludge systems is quantitative monitoring of biomass to keep the cell concentration in an optimum range. In this study,...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7530208/ https://www.ncbi.nlm.nih.gov/pubmed/33042087 http://dx.doi.org/10.3389/fmicb.2020.574966 |
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author | Asgharnejad, Hashem Sarrafzadeh, Mohammad-Hossein |
author_facet | Asgharnejad, Hashem Sarrafzadeh, Mohammad-Hossein |
author_sort | Asgharnejad, Hashem |
collection | PubMed |
description | Activated sludge process is the most common method for biological treatment of industrial and municipal wastewater. One of the most important parameters in performance of activated sludge systems is quantitative monitoring of biomass to keep the cell concentration in an optimum range. In this study, a novel method for activated sludge quantification based on image processing and RGB analysis is proposed. According to the results, the intensity of blue color in the macroscopic image of activated sludge culture can be a very accurate index for cell concentration measurement and R(2) coefficient, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) which are 0.990, 2.000, 0.323, and 13.848, respectively, prove this claim. Besides, in order to avoid the difficulties of working in the three-parameter space of RGB, converting to grayscale space has been applied which can estimate cell concentration with R(2) = 0.99. Ultimately, an exponential correlation between RGB values and cell concentrations in lower amounts of biomass has been proposed based on Beer-Lambert law which can estimate activated sludge biomass concentration with R(2) = 0.97 based on B index. |
format | Online Article Text |
id | pubmed-7530208 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75302082020-10-09 Development of Digital Image Processing as an Innovative Method for Activated Sludge Biomass Quantification Asgharnejad, Hashem Sarrafzadeh, Mohammad-Hossein Front Microbiol Microbiology Activated sludge process is the most common method for biological treatment of industrial and municipal wastewater. One of the most important parameters in performance of activated sludge systems is quantitative monitoring of biomass to keep the cell concentration in an optimum range. In this study, a novel method for activated sludge quantification based on image processing and RGB analysis is proposed. According to the results, the intensity of blue color in the macroscopic image of activated sludge culture can be a very accurate index for cell concentration measurement and R(2) coefficient, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) which are 0.990, 2.000, 0.323, and 13.848, respectively, prove this claim. Besides, in order to avoid the difficulties of working in the three-parameter space of RGB, converting to grayscale space has been applied which can estimate cell concentration with R(2) = 0.99. Ultimately, an exponential correlation between RGB values and cell concentrations in lower amounts of biomass has been proposed based on Beer-Lambert law which can estimate activated sludge biomass concentration with R(2) = 0.97 based on B index. Frontiers Media S.A. 2020-09-18 /pmc/articles/PMC7530208/ /pubmed/33042087 http://dx.doi.org/10.3389/fmicb.2020.574966 Text en Copyright © 2020 Asgharnejad and Sarrafzadeh. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Asgharnejad, Hashem Sarrafzadeh, Mohammad-Hossein Development of Digital Image Processing as an Innovative Method for Activated Sludge Biomass Quantification |
title | Development of Digital Image Processing as an Innovative Method for Activated Sludge Biomass Quantification |
title_full | Development of Digital Image Processing as an Innovative Method for Activated Sludge Biomass Quantification |
title_fullStr | Development of Digital Image Processing as an Innovative Method for Activated Sludge Biomass Quantification |
title_full_unstemmed | Development of Digital Image Processing as an Innovative Method for Activated Sludge Biomass Quantification |
title_short | Development of Digital Image Processing as an Innovative Method for Activated Sludge Biomass Quantification |
title_sort | development of digital image processing as an innovative method for activated sludge biomass quantification |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7530208/ https://www.ncbi.nlm.nih.gov/pubmed/33042087 http://dx.doi.org/10.3389/fmicb.2020.574966 |
work_keys_str_mv | AT asgharnejadhashem developmentofdigitalimageprocessingasaninnovativemethodforactivatedsludgebiomassquantification AT sarrafzadehmohammadhossein developmentofdigitalimageprocessingasaninnovativemethodforactivatedsludgebiomassquantification |